Day: September 6, 2018

Research at Facebook just made it easier to translate between languages without many translation examples. For example, from Urdu to English.

Neural Machine Translation

Neural Machine Translation (NMT) is the field concerned with using AI to translate between any language such as English and French. In 2015 researchers at the Montreal Institute of Learning Algorithms, developed new AI techniques [1] which allowed machine-generated translations to finally work. Almost overnight, systems like Google Translate became orders of magnitude better.

While that leap was significant, it still required having sentence pairs in both languages, for example, “I like to eat” (English) and “me gusta comer” (Spanish). For translations between languages like Urdu and English without many of these pairs, translation systems failed miserably. Since then, researchers have been building systems that can translate without sentence pairings, ie: Unsupervised Neural Machine Translation (UNMT).

In the past year, researchers at Facebook, NYU, University of the Basque Country and Sorbonne Universites, made dramatic advancements which are finally enabling systems to translate without knowing that “house” means “casa” in Spanish.

Just a few days ago, Facebook AI Research (FAIR), published a paper [2] showing a dramatic improvement which allowed translations from languages like Urdu to English. “To give some idea of the level of advancement, an improvement of 1 BLEU point (a common metric for judging the accuracy of MT) is considered a remarkable achievement in this field; our methods showed an improvement of more than 10 BLEU points.”